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Scalable Anomaly Detection for Smart City Infrastructure Networks
Found in: IEEE Internet Computing
By Djellel Eddine Difallah,Philippe Cudre-Mauroux,Sean A. McKenna
Issue Date:November 2013
pp. 39-47
Dynamically detecting anomalies can be difficult in very large-scale infrastructure networks. The authors' approach addresses spatiotemporal anomaly detection in a smarter city context with large numbers of sensors deployed. They propose a scalable, hybrid...
 
FAARM: Frequent Association Action Rules Mining Using FP-Tree
Found in: Data Mining Workshops, International Conference on
By Djellel Eddine Difallah,Ryan G. Benton,Vijay Raghavan,Tom Johnsten
Issue Date:December 2011
pp. 398-404
Action rules mining aims to provide recommendations to analysts seeking to achieve a specific change. An action rule is constructed as a series of changes, or actions, which can be made to some of the flexible characteristics of the information system that...
 
ZenCrowd: leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking
Found in: Proceedings of the 21st international conference on World Wide Web (WWW '12)
By Philippe Cudre-Mauroux, Djellel Eddine Difallah, Gianluca Demartini
Issue Date:April 2012
pp. 469-478
We tackle the problem of entity linking for large collections of online pages; Our system, ZenCrowd, identifies entities from natural language text using state of the art techniques and automatically connects them to the Linked Open Data cloud. We show how...
     
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